CN105678086A - Alternate iterative algorithm for temperature field and concentration field reconstruction based on spectral absorption - Google Patents

Alternate iterative algorithm for temperature field and concentration field reconstruction based on spectral absorption Download PDF

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CN105678086A
CN105678086A CN201610018553.9A CN201610018553A CN105678086A CN 105678086 A CN105678086 A CN 105678086A CN 201610018553 A CN201610018553 A CN 201610018553A CN 105678086 A CN105678086 A CN 105678086A
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周宾
程禾尧
许康
李可
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Southeast University
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Abstract

本发明公开了一种基于光谱吸收的温度场和浓度场重建的交替迭代算法,首先对浓度场的计算提出了线性化方案,将原系统半线性化,从而弱化了原系统的非线性;其次对待测温度场、浓度场提出了交替迭代方案,每一步迭代降低一半的未知变量个数;最后,用优化技术引入惩罚项来克服重建过程的病态性,在每一步迭代时能自动调整正则化参数,保证了迭代解收敛于精确解。本发明提出的交替迭代方案在保持重建精度的前提下,能够显著地缩短计算时间,并且适用于大规模的场反演计算。

The invention discloses an alternate iterative algorithm for reconstruction of temperature field and concentration field based on spectral absorption. First, a linearization scheme is proposed for the calculation of concentration field, and the original system is semi-linearized, thereby weakening the nonlinearity of the original system; secondly An alternate iteration scheme is proposed for the measured temperature field and concentration field, and the number of unknown variables is reduced by half in each step of iteration; finally, a penalty term is introduced by optimization technology to overcome the ill-conditioned nature of the reconstruction process, and the regularization can be automatically adjusted in each step of iteration parameter, which ensures that the iterative solution converges to the exact solution. The alternate iteration scheme proposed by the invention can significantly shorten the calculation time under the premise of maintaining the reconstruction accuracy, and is suitable for large-scale field inversion calculation.

Description

一种基于光谱吸收的温度场和浓度场重建的交替迭代算法An Alternate Iterative Algorithm for Reconstruction of Temperature Field and Concentration Field Based on Spectral Absorption

技术领域technical field

本发明涉及一种基于光谱吸收的温度场和浓度场重建的交替迭代算法,属于激光吸收光谱领域。The invention relates to an alternate iterative algorithm for reconstruction of temperature field and concentration field based on spectral absorption, belonging to the field of laser absorption spectroscopy.

背景技术Background technique

近年来,随着国家对于环境保护的日趋重视,以及出于保证工业生产安全高效进行的需要,光学非接触式的气体检测技术发展十分迅速。基于激光吸收光谱的气体检测技术具有无需预处理、响应快速、数据准确、多参数同时检测等优势,成为目前应用于众多领域的现场在线检测技术之一。In recent years, with the country's increasing emphasis on environmental protection and the need to ensure safe and efficient industrial production, optical non-contact gas detection technology has developed rapidly. Gas detection technology based on laser absorption spectroscopy has the advantages of no preprocessing, fast response, accurate data, and simultaneous detection of multiple parameters, and has become one of the on-site on-line detection technologies currently used in many fields.

吸收光谱技术使用激光穿过待测流场区域,当激光频率与气体吸收组分的跃迁频率相同时,激光能量将被吸收,通过对比入射光强与透射光强可以得到沿光路径的吸收值,进而确定气体温度和浓度等物性参数。然而激光吸收光谱技术的测量结果反映的是一个区域的温度或浓度平均值,不适合于具有显著温度、浓度梯度的测量环境。因此,探索和发展基于吸收光谱技术的非均匀流场参数测量方法具有重要的意义。Absorption spectroscopy technology uses a laser to pass through the area of the flow field to be measured. When the laser frequency is the same as the transition frequency of the gas absorption component, the laser energy will be absorbed. By comparing the incident light intensity with the transmitted light intensity, the absorption value along the optical path can be obtained. , and then determine the physical parameters such as gas temperature and concentration. However, the measurement results of laser absorption spectroscopy reflect the average temperature or concentration of an area, which is not suitable for measurement environments with significant temperature and concentration gradients. Therefore, it is of great significance to explore and develop the measurement method of non-uniform flow field parameters based on absorption spectroscopy.

目前国内外科研机构对高温反应流的非均匀场参数分布测量已经开展了一定的研究,基于不同原理的测量方法各有利弊。有限范围直接重建方法利用基函数离散被测区域,适用于平滑分布的流场,不适合待测区域存在突变的情况。滤波反投影算法在大量投影光线和均匀的投影角度下可以得到精度较高的重建结果,但是在实际燃烧场测量中投影光线角度和数目受到空间可用性和系统复杂性的限制。代数迭代算法是一种基于迭代求解策略的寻优算法,可以用于不完全的投影数据或者投影为非均匀分布的情形,计算速度较快,但是需要增加不同方向上的投影数,无法同时利用多条吸收谱线的信息。序列二次规划算法具备整体收敛性的同时保持局部超1次的收敛性,搜索效率较高,但是其对于初值异常敏感,容易陷入局部最优而得不到全局最优解。模拟退火算法通过增加单光路上气体吸收谱线测量值来提高温度场和浓度场重建结果的精度和稳定性,整体重建效果优于上述算法,但是其属于随机搜索优化类算法,计算效率较低、耗时过长。At present, scientific research institutions at home and abroad have carried out some research on the measurement of non-uniform field parameter distribution of high-temperature reaction flow, and the measurement methods based on different principles have their own advantages and disadvantages. The limited-range direct reconstruction method uses basis functions to discretize the measured area, which is suitable for smooth distribution of the flow field, but not suitable for the situation where there is a sudden change in the measured area. The filtered back-projection algorithm can obtain high-precision reconstruction results under a large number of projection rays and uniform projection angles, but the angle and number of projection rays are limited by space availability and system complexity in actual combustion field measurements. The algebraic iterative algorithm is an optimization algorithm based on an iterative solution strategy. It can be used for incomplete projection data or projections with non-uniform distribution. The calculation speed is fast, but it needs to increase the number of projections in different directions and cannot be used at the same time. Information about multiple absorption lines. The sequential quadratic programming algorithm has overall convergence while maintaining local super-1 convergence, and has high search efficiency, but it is extremely sensitive to the initial value, and it is easy to fall into the local optimum and fail to obtain the global optimal solution. The simulated annealing algorithm improves the accuracy and stability of the temperature field and concentration field reconstruction results by increasing the measured value of the gas absorption spectrum on a single optical path. The overall reconstruction effect is better than the above algorithm, but it belongs to the random search optimization algorithm, and the calculation efficiency is low. , Time-consuming.

发明内容Contents of the invention

本发明所要解决的技术问题是提供一种基于光谱吸收的温度场和浓度场重建的交替迭代算法。The technical problem to be solved by the present invention is to provide an alternate iterative algorithm for reconstruction of temperature field and concentration field based on spectral absorption.

为解决上述技术问题,本发明所采用的技术方案如下:In order to solve the problems of the technologies described above, the technical scheme adopted in the present invention is as follows:

一种基于光谱吸收的温度场和浓度场重建的交替迭代算法,包括如下步骤:An alternate iterative algorithm for reconstruction of temperature field and concentration field based on spectral absorption, including the following steps:

步骤一,待测高温气体流经二维矩形区域,记该待测区域为D={(x,y):0<x<L,0<y<W},温度场为T(x,y),浓度场为X(x,y),通过区域D的激光测量值与区域D内温度场和浓度场之间的关系用式(1)表示:Step 1, the high-temperature gas to be measured flows through a two-dimensional rectangular area, and the area to be measured is recorded as D={(x, y): 0<x<L, 0<y<W}, and the temperature field is T(x, y ), the concentration field is X(x, y), the relationship between the measured value of the laser passing through area D and the temperature field and concentration field in area D is expressed by formula (1):

式中,A(y0,v0)是中心频率为v0的入射激光沿路径y=y0∈(0,W)的积分吸收面积测量值,B(x0,v0)是沿路径x=x0∈(0,L)的积分吸收面积测量值,P是区域D上的气体压力,S(T(x,y0),v0)是温度为T(x,y0)、频率为v0的谱线线强;where A(y 0 , v 0 ) is the measured value of the integrated absorption area of the incident laser with center frequency v 0 along the path y=y 0 ∈ (0, W), B(x 0 , v 0 ) is the x = x 0 ∈ (0, L) integral absorption area measurement, P is the gas pressure on region D, S(T(x, y 0 ), v 0 ) is the temperature T(x, y 0 ), the intensity of the spectral line at frequency v 0 ;

步骤二、根据式(1)求解(X(x,y),T(x,y)):Step 2. Solve (X(x, y), T(x, y)) according to formula (1):

1)假设(X*(x,y),T*(x,y))是满足系统的精确解,同时给出(X*(x,y),T*(x,y))的一个先验近似值以及迭代初始值(X0(x,y),T0(x,y)),并给出最大迭代次数Nmax、正则化参数μ,β>0、迭代终止水平ε>0和容许集合Xrange×Trange,设置n的初始值为0;1) Assume that (X * (x, y), T * (x, y)) is an exact solution that satisfies the system, and give (X * (x, y), T * (x, y)) a prior Proximity And the initial value of iteration (X 0 (x, y), T 0 (x, y)), and give the maximum number of iterations N max , regularization parameter μ, β>0, iteration termination level ε>0 and the allowable set X range ×T range , set the initial value of n to 0;

2)对于已知的Tn(x,y),通过对下式进行离散后正则化求解可得Xn+1(x,y):2) For the known T n (x, y), X n+1 (x, y) can be obtained by regularizing the following formula after discretization:

式中,表示迭代时使用的算子;若Xn+1(x,y)∈Xrange,取μ=μ0并跳出此次迭代;否则更新μ←2μ,再次计算Xn+1(x,y);In the formula, Indicates the operator used during iteration; if X n+1 (x, y)∈X range , take μ=μ 0 and jump out of this iteration; otherwise update μ←2μ, and calculate X n+1 (x, y) again ;

3)对于已知的Xn+1(x,y),通过对下式进行离散后正则化求解可得Tn+1(x,y):3) For the known X n+1 (x, y), T n+1 (x, y) can be obtained by regularizing the following formula after discretization:

式中,表示迭代时使用的算子;若Tn+1(x,y)∈Trange,取β=β0并跳出此次迭代,否则更新β←2β,再次计算Tn+1(x,y);In the formula, Indicates the operator used during iteration; if T n+1 (x, y)∈T range , take β=β 0 and jump out of this iteration, otherwise update β←2β, and calculate T n+1 (x, y) again ;

4)对于足够大的数n,满足终止准则:4) For a sufficiently large number n, the termination criterion is met:

||(Xn+1,Tn+1)-(Xn,Tn)||D<ε(4);||(X n+1 ,T n+1 )-(X n ,T n )|| D <ε(4);

或n=Nmax则迭代终止,(Xn+1,Tn+1)作为浓度场和温度场最终解;否则更新Tn←Tn+1、n←n+1,重复步骤2)~4)。or n=N max , the iteration terminates, and (X n+1 , T n+1 ) is used as the final solution of the concentration field and temperature field; otherwise, update T n ←T n+1 , n←n+1, and repeat step 2)~ 4).

为了提高重构效果,本发明提出在待测区域的每一个方向上,充分利用包含多条气体特征吸收谱线的信息,选取第r条气体特征吸收谱线对应的中心频率记为vr,式(2.1)、式(2.2)、式(3.1)、式(3.2)以及(A,B)依赖于vr,从而式(2.1)、式(2.2)、式(3.1)和式(3.2)中每一步迭代分别可以用式(5.1)、式(5.2)、式(6.1)和式(6.2)替代:In order to improve the reconstruction effect, the present invention proposes to make full use of the information including multiple gas characteristic absorption lines in each direction of the region to be measured, and select the center frequency corresponding to the rth gas characteristic absorption line as v r , Equation (2.1), Equation (2.2), Equation (3.1), Equation (3.2) and (A, B) depend on v r , so Equation (2.1), Equation (2.2), Equation (3.1) and Equation (3.2) Each step of iteration can be replaced by formula (5.1), formula (5.2), formula (6.1) and formula (6.2):

对待测二维区域进行网格离散化处理,并采用自适应迭代方法来求解每个网格内的浓度和温度,即Xn+1(x,y)和Tn+1(x,y):Perform grid discretization in the two-dimensional area to be measured, and use an adaptive iterative method to solve the concentration and temperature in each grid, that is, X n+1 (x, y) and T n+1 (x, y) :

1)根据待测二维区域D的形状和大小,将待测二维区域划分成M行和N列的网格,令M=N,且每个网格分别对应一个浓度和温度待测值,从光谱数据库中选择I条气体特征吸收谱线,并且I≥[2×M×N/(M+N)],r的取值为1至I之间的整数;1) According to the shape and size of the two-dimensional area D to be measured, divide the two-dimensional area to be measured into grids of M rows and N columns, let M=N, and each grid corresponds to a concentration and temperature to be measured , select I gas characteristic absorption line from spectral database, and I≥[2×M×N/(M+N)], the value of r is an integer between 1 and 1;

2)式(5.2)写成:2) Formula (5.2) is written as:

EgS(T,vr)X=P(vr)(7);EgS(T,v r )X=P(v r )(7);

式中,P(vr)为谱线vr对应的测量值投影向量,E=(e(i,j))是2N×N2维的0-1矩阵,其中e(i,j)表示激光是否通过第i个方向上的第j个格子;即第i个方向上的激光通过第j个格子时,令e(i,j)=1,否则e(i,j)=0;In the formula, P(v r ) is the measured value projection vector corresponding to the spectral line v r , E=(e( i, j) ) is a 2N×N 2 -dimensional 0-1 matrix, where e (i, j) represents Whether the laser passes through the j-th grid in the i-th direction; that is, when the laser in the i-th direction passes through the j-th grid, let e (i, j) = 1, otherwise e (i, j) = 0;

式(7)的显式解表示为:The explicit solution of formula (7) is expressed as:

其中,in,

通过式(8),由Tn(x,y)计算得到Xn+1(x,y);Through formula (8), X n+1 (x, y) can be calculated from T n (x, y);

3)由步骤2)计算得到的Xn+1(x,y)作为已知量,使用非线性最小二乘寻优算法对式(6.1)求解可得Tn+1(x,y)。3) X n+1 (x, y) calculated from step 2) is used as a known quantity, and T n+1 (x, y) can be obtained by solving formula (6.1) using nonlinear least squares optimization algorithm.

其中为了确保迭代解的数值收敛性,给定X(x,y)和T(x,y)的容许集合Xrange×Trange,使其包含了精确解X*(x,y)和T*(x,y),同时引进带有正则化参数μ,β的罚项来克服重建过程的病态性,在每一步迭代中自动调整正则化参数μ,β,从而保证迭代解收敛于精确解。In order to ensure the numerical convergence of the iterative solution, the admissible set X range ×T range of X(x, y) and T(x, y) is given, so that it contains the exact solution X * (x, y) and T * (x, y), while introducing penalties with regularization parameters μ, β to overcome the ill-conditioned nature of the reconstruction process, and automatically adjust the regularization parameters μ, β in each step of iteration, so as to ensure that the iterative solution converges to the exact solution.

有益效果:本发明算法可以解决采用吸收光谱数据来重建温度场和浓度场时的非线性问题,同时利用优化技术引入惩罚项来克服重建过程中的病态性,不仅能够充分利用多光谱测量信息,而且在保证重建质量的同时能显著缩短计算时间。Beneficial effects: the algorithm of the present invention can solve the non-linear problem when using absorption spectrum data to reconstruct the temperature field and concentration field, and at the same time use optimization technology to introduce penalty items to overcome the ill-conditionedness in the reconstruction process, not only can make full use of multi-spectral measurement information, Moreover, the calculation time can be significantly shortened while maintaining the reconstruction quality.

附图说明Description of drawings

图1是本发明算法的流程图;Fig. 1 is the flowchart of algorithm of the present invention;

图2是本发明算法中待测区域网格划分的示意图;Fig. 2 is the schematic diagram of the grid division of the region to be measured in the algorithm of the present invention;

图3是本发明仿真实施例中设定的浓度场模型图;Fig. 3 is the concentration field model diagram set in the simulation embodiment of the present invention;

图4是本发明仿真实施例中设定的温度场模型图;Fig. 4 is the temperature field model diagram of setting in the simulation embodiment of the present invention;

图5是本发明算法重建浓度场的结果图;Fig. 5 is the result figure of the algorithm reconstruction concentration field of the present invention;

图6是本发明算法重建温度场的结果图;Fig. 6 is the result figure of the algorithm reconstruction temperature field of the present invention;

图7是模拟退火算法重建浓度场的结果图;Fig. 7 is the result diagram of reconstructing the concentration field by the simulated annealing algorithm;

图8是模拟退火算法重建温度场的结果图;Fig. 8 is a result diagram of reconstructing the temperature field by the simulated annealing algorithm;

图9是本发明提出的算法和模拟退火算法在不同噪声程度下重建温度场的均方根误差图。Fig. 9 is the root mean square error diagram of the reconstruction temperature field under different noise levels by the algorithm proposed by the present invention and the simulated annealing algorithm.

具体实施方式detailed description

以下结合附图对本发明进行详细描述。The present invention will be described in detail below in conjunction with the accompanying drawings.

如图1所示,本发明基于光谱吸收的温度场和浓度场重建的交替迭代算法,包括如下实施步骤:As shown in Figure 1, the present invention is based on the alternating iterative algorithm of spectral absorption temperature field and concentration field reconstruction, including the following implementation steps:

步骤一、假设待测高温气体流经二维矩形区域,不同频率的激光从该区域的侧面入射,并在对面得到相应的经气体吸收后的激光,记该待测区域为D={(x,y):0<x<L,0<y<W},温度场为T(x,y),浓度场为X(x,y),采用的气体特征吸收谱线对应的中心频率为v0。沿光路径y=y0∈(0,W)的能量吸收表示为:Step 1. Assuming that the high-temperature gas to be measured flows through a two-dimensional rectangular area, lasers of different frequencies are incident from the side of the area, and the corresponding lasers absorbed by the gas are obtained on the opposite side, and the area to be measured is recorded as D={(x , y): 0<x<L, 0<y<W}, the temperature field is T(x, y), the concentration field is X(x, y), and the center frequency corresponding to the gas characteristic absorption line is v 0 . The energy absorption along the optical path y = y 0 ∈ (0, W) is expressed as:

式中,I(L,y0,v0)是沿着y=y0在x=L处得到的透射光强,对应于激光入射光强I(0,y0,v0);α(y0,v,v0)是入射激光在路径y=y0处的吸光度;P是区域D上的气体压力;φ(v-v0)是所选谱线对应的线型函数在频率v处的值,根据测量环境中的温度、压力条件从Gauss线型、Lorentz线型和Voigt线型中选择其中一种,并且满足S(T(x,y0),v0)是温度为T(x,y0)、频率为v0的谱线线强,可表示为:In the formula, I(L, y 0 , v 0 ) is the transmitted light intensity obtained at x=L along y=y 0 , corresponding to the laser incident light intensity I(0, y 0 , v 0 ); α( y 0 , v, v 0 ) is the absorbance of the incident laser at the path y=y 0 ; P is the gas pressure on the area D; φ(vv 0 ) is the line function corresponding to the selected spectral line at the frequency v Value, according to the temperature and pressure conditions in the measurement environment, choose one of the Gauss line type, Lorentz line type and Voigt line type, and satisfy S(T(x, y 0 ), v 0 ) is the spectral line intensity at temperature T(x, y 0 ) and frequency v 0 , which can be expressed as:

式中,参考温度T0=296K,h是普朗克常数,c是光速,E″是低状态能级,k是波尔兹曼常数。分子配分函数Q(T)近似描述为:In the formula, the reference temperature T 0 =296K, h is Planck’s constant, c is the speed of light, E″ is the low-state energy level, and k is Boltzmann’s constant. The molecular partition function Q(T) is approximately described as:

Q(T)=a+bT+cT2+dT3(3);Q(T)=a+bT+cT 2 +dT 3 (3);

系数(a,b,c,d)依赖于所属的温度范围;The coefficients (a, b, c, d) depend on the temperature range to which they belong;

那么沿光路径y=y0∈(0,W)的积分吸收面积表示为:Then the integrated absorption area along the light path y=y 0 ∈ (0, W) is expressed as:

类似地,沿光路径x=x0∈(0,L)的能量吸收满足:Similarly, energy absorption along the light path x = x 0 ∈ (0, L) satisfies:

进而沿该路径的积分吸收面积表示为:The integrated absorption area along this path is then expressed as:

其中,A(y0,v0)和B(x0,v0)的值可以通过实验获取;Among them, the values of A(y 0 , v 0 ) and B(x 0 , v 0 ) can be obtained through experiments;

步骤二、通过求解式(7):Step 2, by solving formula (7):

可以得到区域D内的浓度场X(x,y)和温度场T(x,y);观察该系统,可以得出:The concentration field X(x, y) and temperature field T(x, y) in the area D can be obtained; observing the system, it can be concluded that:

1)虽然式(7)关于(X(x,y),T(x,y))是非线性的,但若T(x,y)给定,则式(7)关于X(x,y)为线性的;1) Although formula (7) is nonlinear with respect to (X(x, y), T(x, y)), if T(x, y) is given, then formula (7) with respect to X(x, y) is linear;

2)对于给定的T(x,y),式(7)关于X(x,y)是不稳定的,即(A,B)的微小扰动,都将导致X(x,y)很大的变化;2) For a given T(x, y), formula (7) is unstable with respect to X(x, y), that is, a small disturbance of (A, B) will cause X(x, y) to be very large The change;

3)对于给定的X(x,y),式(7)关于T(x,y)仍然是非线性的;3) For a given X(x, y), formula (7) is still nonlinear with respect to T(x, y);

根据该系统的特点,求解(X(x,y),T(x,y)):According to the characteristics of the system, solve (X(x, y), T(x, y)):

1)假设(X*(x,y),T*(x,y))是满足系统的精确解,同时给出(X*(x,y),T*(x,y))的一个先验近似值以及迭代初始值(X0(x,y),T0(x,y)),并给出最大迭代次数Nmax、正则化参数μ,β>0、迭代终止水平ε>0和容许集合Xrange×Trange,设置n的初始值为0;1) Assume that (X * (x, y), T * (x, y)) is an exact solution that satisfies the system, and give (X * (x, y), T * (x, y)) a prior Proximity And the initial value of iteration (X 0 (x, y), T 0 (x, y)), and give the maximum number of iterations N max , regularization parameter μ, β>0, iteration termination level ε>0 and the allowable set X range ×T range , set the initial value of n to 0;

2)对于已知的Tn(x,y),通过对下式进行离散后正则化求解可得Xn+1(x,y):2) For the known T n (x, y), X n+1 (x, y) can be obtained by regularizing the following formula after discretization:

式中,表示迭代时使用的算子;若Xn+1(x,y)∈Xrange,取μ=μ0并跳出此次迭代;否则更新μ←2μ,再次计算Xn+1(x,y);In the formula, Indicates the operator used during iteration; if X n+1 (x, y)∈X range , take μ=μ 0 and jump out of this iteration; otherwise update μ←2μ, and calculate X n+1 (x, y) again ;

3)对于已知的Xn+1(x,y),通过对下式进行离散后正则化求解可得Tn+1(x,y):3) For the known X n+1 (x, y), T n+1 (x, y) can be obtained by regularizing the following formula after discretization:

式中,表示迭代时使用的算子;若Tn+1(x,y)∈Trange,取β=β0并跳出此次迭代,否则更新β←2β,再次计算Tn+1(x,y);In the formula, Indicates the operator used during iteration; if T n+1 (x, y)∈T range , take β=β 0 and jump out of this iteration, otherwise update β←2β, and calculate T n+1 (x, y) again ;

4)对于足够大的数n,满足终止准则:4) For a sufficiently large number n, the termination criterion is satisfied:

||(Xn+1,Tn+1)-(Xn,Tn)||D<ε(10);||(X n+1 ,T n+1 )-(X n ,T n )|| D <ε(10);

或n=Nmax则迭代终止,(Xn+1,Tn+1)作为浓度场和温度场最终解;否则更新Tn←Tn +1、n←n+1,重复步骤2~4。Or if n=N max , the iteration terminates, and (X n+1 , T n+1 ) is used as the final solution of the concentration field and temperature field; otherwise, update T n ←T n +1 , n←n+1, and repeat steps 2 to 4 .

步骤三、为了提高重构效果,本发明提出在待测区域的每一个方向上,充分利用包含多条气体特征吸收谱线的信息,选取的第r条气体特征吸收谱线对应的中心频率记为vr。式(8)和(9)以及(A,B)依赖于vr,从而式(8)和(9)中的每一步迭代可以用:Step 3. In order to improve the reconstruction effect, the present invention proposes that in each direction of the region to be measured, the information containing a plurality of gas characteristic absorption lines is fully utilized, and the center frequency corresponding to the selected rth gas characteristic absorption line is recorded as is v r . Equations (8) and (9) and (A, B) depend on v r , so that each iteration step in Equations (8) and (9) can be used:

来代替;to replace;

步骤四、对待测二维区域进行网格离散化处理,并采用自适应迭代方法来求解每个网格内的浓度和温度:Step 4. Perform grid discretization in the two-dimensional area to be measured, and use an adaptive iterative method to solve the concentration and temperature in each grid:

1)根据待测二维区域D的形状和大小,将待测二维区域划分成M行和N列的网格,令M=N,且每个网格分别对应一个浓度和温度待测值。从光谱数据库中选择I条气体特征吸收谱线,并且I≥[2×M×N/(M+N)],r的取值为1至I之间的整数;1) According to the shape and size of the two-dimensional area D to be measured, divide the two-dimensional area to be measured into grids of M rows and N columns, let M=N, and each grid corresponds to a concentration and temperature to be measured . Select 1 gas characteristic absorption lines from the spectral database, and I≥[2×M×N/(M+N)], the value of r is an integer between 1 and 1;

2)式(11.2)可以写成:2) Formula (11.2) can be written as:

EgS(T,vr)X=P(vr)(13); EgS (T,vr)X=P( vr )(13);

式中,P(vr)为谱线vr对应的测量值投影向量,E=(e(i,j))是2N×N2维的0-1矩阵,其中e(i,j)表示激光是否通过第i个方向上的第j个格子,即第i个方向上的激光通过第j个格子时,令e(i,j)=1,否则e(i,j)=0;In the formula, P(v r ) is the measured value projection vector corresponding to the spectral line v r , E=(e (i, j) ) is a 2N×N 2 -dimensional 0-1 matrix, where e (i, j) represents Whether the laser passes through the j-th grid in the i-th direction, that is, when the laser in the i-th direction passes through the j-th grid, set e (i, j) = 1, otherwise e (i, j) = 0;

从而式(13)的显式解表示为:So the explicit solution of formula (13) is expressed as:

其中,in,

通过式(14),可由Tn(x,y)计算得到Xn+1(x,y);Through formula (14), X n+1 (x, y) can be calculated from T n (x, y);

3)由步骤2计算得到的Xn+1(x,y)作为已知量,使用非线性最小二乘寻优算法对式(12)求解可得Tn+1(x,y)。3) X n+1 (x, y) calculated in step 2 is used as a known quantity, and T n+1 (x, y) can be obtained by solving equation (12) using the nonlinear least squares optimization algorithm.

其中为了确保迭代解的数值收敛性,给定X(x,y)和T(x,y)的容许集合Xrange×Trange,使其包含了精确解X*(x,y)和T*(x,y),同时引进带有正则化参数μ,β的罚项来克服重建过程的病态性,在每一步迭代中自动调整正则化参数μ,β,从而保证迭代解收敛于精确解。In order to ensure the numerical convergence of the iterative solution, the admissible set X range ×T range of X(x, y) and T(x, y) is given, so that it contains the exact solution X * (x, y) and T * (x, y), while introducing penalties with regularization parameters μ, β to overcome the ill-conditioned nature of the reconstruction process, and automatically adjust the regularization parameters μ, β in each step of iteration, so as to ensure that the iterative solution converges to the exact solution.

仿真实施例Simulation example

为检验本发明算法的性能,本发明模拟了实际应用场合中常见的温度和浓度模型,并将本发明重建结果与模拟退火算法结果作比较。In order to test the performance of the algorithm of the present invention, the present invention simulates common temperature and concentration models in practical applications, and compares the reconstructed results of the present invention with the simulated annealing algorithm results.

待测二维矩形区域的温度范围为1000~1500K,水蒸气体积浓度范围为0~0.2,采用的分布模型为双峰曲面,模型的构建使用高斯曲面和抛物曲面叠加实现,表达式见式(16):The temperature range of the two-dimensional rectangular area to be measured is 1000-1500K, and the water vapor volume concentration range is 0-0.2. The distribution model adopted is a bimodal surface, and the model is constructed by superposition of a Gaussian surface and a parabolic surface. The expression is shown in the formula ( 16):

式中,f(x,y)是待测区域的温度场或浓度场,(x0,y0,z0)是高斯曲面和抛物曲面的峰值点位置,p1、p2、K、b1、b2、c1、c2均是仿真时设定的参数。In the formula, f(x, y) is the temperature field or concentration field of the area to be measured, (x 0 , y 0 , z 0 ) is the peak point position of the Gaussian surface and the parabolic surface, p 1 , p 2 , K, b 1 , b 2 , c 1 , and c 2 are all parameters set during simulation.

如图2所示,将待测区域进行离散成10×10的网格,为使方程组满足封闭求解条件,选用的吸收谱线数目需满足I≥10,这里选择10条水蒸气特征吸收谱线,各条谱线的具体信息见表1;按照双峰曲面模型设定的温度场和浓度场分布见图3~图4,采用本发明提出的算法和模拟退火算法重建的温度场和浓度场结果见图5~图8;As shown in Figure 2, the area to be measured is discretized into 10×10 grids. In order to make the equations meet the closed solution conditions, the number of absorption lines selected must satisfy I≥10. Here, 10 characteristic absorption spectra of water vapor are selected. The specific information of each spectral line is shown in Table 1; the temperature field and concentration field distribution set according to the bimodal surface model are shown in Fig. 3-Fig. Field results are shown in Figures 5 to 8;

表1:本发明算法进行仿真实施例时选用的10条H2O的吸收谱线信息Table 1: The absorption spectrum information of 10 H2O selected when the algorithm of the present invention carries out the simulation embodiment

从图5~图8可以看出,双峰曲面模型下,分别采用交替迭代算法和模拟退火算法重建的温度场和浓度场均与设定值保持一致,都可以实现较高的重建精度。而本发明提出的交替迭代算法计算时间为6.08s,远小于模拟退火算法的计算时间40238.33s。From Figures 5 to 8, it can be seen that under the bimodal surface model, the temperature field and concentration field reconstructed by the alternating iterative algorithm and the simulated annealing algorithm respectively are consistent with the set values, and high reconstruction accuracy can be achieved. However, the calculation time of the alternate iterative algorithm proposed by the present invention is 6.08s, which is much shorter than the calculation time of the simulated annealing algorithm, which is 40238.33s.

此外,在实际的测量过程中不可避免地会存在噪声的干扰。为验证本发明提出的交替迭代算法的抗噪声能力,在双峰曲面模型获得的投影吸收面积上添加不同比例的高斯白噪声,并利用添加了噪声后的数据进行温度场和浓度场重建。为方便对重建结果进行比较,定义均方根误差作为评价依据:In addition, there will inevitably be noise interference in the actual measurement process. In order to verify the anti-noise ability of the alternate iterative algorithm proposed by the present invention, different proportions of Gaussian white noise are added to the projected absorption area obtained by the bimodal surface model, and the temperature field and concentration field are reconstructed by using the noise-added data. In order to facilitate the comparison of reconstruction results, the root mean square error is defined as the evaluation basis:

式中,fi,j是第i个方向上第j个格子处的温度值或浓度值,f0(i,j)是对应于fi,j的设定值。重建的均方根误差大小如图9所示。由图9可以看出,交替迭代算法在重建温度场时较为稳定,其抗噪声能力明显高于模拟退火算法。综合考虑重建温度场和浓度场的整体效果,本发明提出的交替迭代算法在保证重建质量的同时具有较强的抗噪声干扰能力,并且适合于大规模的场反演计算。In the formula, f i, j is the temperature value or concentration value at the jth grid in the i-th direction, and f 0(i, j) is the set value corresponding to f i, j . The root mean square error of the reconstruction is shown in Figure 9. It can be seen from Figure 9 that the alternate iterative algorithm is relatively stable when reconstructing the temperature field, and its anti-noise ability is significantly higher than that of the simulated annealing algorithm. Comprehensively considering the overall effect of reconstructing the temperature field and the concentration field, the alternate iterative algorithm proposed by the invention has strong anti-noise ability while ensuring the reconstruction quality, and is suitable for large-scale field inversion calculation.

本发明算法首先对浓度场的计算提出了线性化方案,将原系统半线性化,从而弱化了原系统的非线性;其次对待测温度场、浓度场提出了交替迭代方案,每一步迭代降低一半的未知变量个数;最后,用优化技术引入惩罚项来克服重建过程的病态性,在每一步迭代时能自动调整正则化参数,保证了迭代解收敛于精确解。本发明提出的交替迭代算法在保持重建精度的前提下,能够显著地缩短计算时间,并且适用于大规模的场反演计算。The algorithm of the present invention first proposes a linearization scheme for the calculation of the concentration field, and semi-linearizes the original system, thus weakening the nonlinearity of the original system; secondly, an alternate iteration scheme is proposed for the measured temperature field and concentration field, and each iteration is reduced by half The number of unknown variables; finally, the optimization technique is used to introduce a penalty term to overcome the ill-conditioned nature of the reconstruction process, and the regularization parameters can be automatically adjusted at each iteration to ensure that the iterative solution converges to the exact solution. The alternate iterative algorithm proposed by the invention can significantly shorten the calculation time under the premise of maintaining the reconstruction accuracy, and is suitable for large-scale field inversion calculation.

Claims (4)

1.一种基于光谱吸收的温度场和浓度场重建的交替迭代算法,其特征在于,包括如下步骤:1. An alternate iterative algorithm based on spectral absorption temperature field and concentration field reconstruction, is characterized in that, comprises the steps: 步骤一、待测高温气体流经二维矩形区域,记该待测区域为D={(x,y):0<x<L,0<y<W},温度场为T(x,y),浓度场为X(x,y),通过区域D的激光测量值与区域D内温度场和浓度场之间的关系用式(1)表示:Step 1. The high-temperature gas to be measured flows through a two-dimensional rectangular area, and the area to be measured is recorded as D={(x, y): 0<x<L, 0<y<W}, and the temperature field is T(x, y ), the concentration field is X(x, y), the relationship between the measured value of the laser passing through area D and the temperature field and concentration field in area D is expressed by formula (1): PP &Integral;&Integral; 00 LL Xx (( xx ,, ythe y 00 )) SS (( TT (( xx ,, ythe y 00 )) ,, vv 00 )) dd xx == AA (( ythe y ,, vv 00 )) ,, ythe y 00 &Element;&Element; (( 00 ,, WW )) PP &Integral;&Integral; 00 WW Xx (( xx 00 ,, ythe y )) SS (( TT (( xx 00 ,, ythe y )) ,, vv 00 )) dd ythe y == BB (( xx ,, vv 00 )) ,, xx 00 &Element;&Element; (( 00 ,, LL )) -- -- -- (( 11 )) ;; 式中,A(y0,v0)是中心频率为v0的入射激光沿路径y=y0∈(0,W)的积分吸收面积测量值,B(x0,v0)是沿路径x=x0∈(0,L)的积分吸收面积测量值,P是区域D上的气体压力,S(T(x,y0),v0)是温度为T(x,y0)、频率为v0的谱线线强;where A(y 0 , v 0 ) is the measured value of the integrated absorption area of the incident laser with center frequency v 0 along the path y=y 0 ∈ (0, W), B(x 0 , v 0 ) is the x = x 0 ∈ (0, L) integral absorption area measurement, P is the gas pressure on region D, S(T(x, y 0 ), v 0 ) is the temperature T(x, y 0 ), the intensity of the spectral line at frequency v 0 ; 步骤二、根据式(1)求解(X(x,y),T(x,y)):Step 2. Solve (X(x, y), T(x, y)) according to formula (1): 1)假设(X*(x,y),T*(x,y))是满足系统的精确解,同时给出(X*(x,y),T*(x,y))的一个先验近似值以及迭代初始值(X0(x,y),T0(x,y)),并给出最大迭代次数Nmax、正则化参数μ,β>0、迭代终止水平ε>0和容许集合Xrange×Trange,设置n的初始值为0;1) Assume that (X * (x, y), T * (x, y)) is an exact solution that satisfies the system, and give (X * (x, y), T * (x, y)) a prior Proximity And the initial value of iteration (X 0 (x, y), T 0 (x, y)), and give the maximum number of iterations N max , regularization parameter μ, β>0, iteration termination level ε>0 and the allowable set X range ×T range , set the initial value of n to 0; 2)对于已知的Tn(x,y),通过对下式进行离散后正则化求解可得Xn+1(x,y):2) For the known T n (x, y), X n+1 (x, y) can be obtained by regularizing the following formula after discretization: TT nno ++ 11 (( xx ,, ythe y )) == argarg minmin Xx {{ || || KK LL nno &CenterDot;&Center Dot; Xx -- AA || || (( 00 ,, WW )) 22 ++ || || KK WW nno &CenterDot;&Center Dot; Xx -- BB || || (( 00 ,, LL )) 22 ++ &mu;&mu; || || Xx -- Xx &OverBar;&OverBar; || || DD. 22 }} -- -- -- (( 2.12.1 )) ;; (( KK LL nno &CenterDot;&Center Dot; Xx )) (( ythe y 00 )) == PP &Integral;&Integral; 00 LL Xx (( xx ,, ythe y 00 )) SS (( TT nno (( xx ,, ythe y 00 )) ,, vv 00 )) dd xx == AA (( ythe y 00 ,, vv 00 )) ,, ythe y 00 &Element;&Element; (( 00 ,, WW )) (( KK WW nno &CenterDot;&Center Dot; Xx )) (( xx 00 )) == PP &Integral;&Integral; 00 WW Xx (( xx 00 ,, ythe y )) SS (( TT nno (( xx 00 ,, ythe y )) ,, vv 00 )) dd ythe y == BB (( xx 00 ,, vv 00 )) ,, xx 00 &Element;&Element; (( 00 ,, LL )) -- -- -- (( 2.22.2 )) ;; 式中,表示迭代时使用的算子;若Xn+1(x,y)∈Xrange,取μ=μ0并跳出此次迭代;否则更新μ←2μ,再次计算Xn+1(x,y);In the formula, Indicates the operator used during iteration; if X n+1 (x, y)∈X range , take μ=μ 0 and jump out of this iteration; otherwise update μ←2μ, and calculate X n+1 (x, y) again ; 3)对于已知的Xn+1(x,y),通过对下式进行离散后正则化求解可得Tn+1(x,y):3) For the known X n+1 (x, y), T n+1 (x, y) can be obtained by regularizing the following formula after discretization: TT nno ++ 11 (( xx ,, ythe y )) == argarg minmin TT {{ || || GG LL nno ++ 11 &CenterDot;&CenterDot; TT -- AA || || (( 00 ,, WW )) 22 ++ || || GG WW nno ++ 11 &CenterDot;&CenterDot; TT -- BB || || (( 00 ,, LL )) 22 ++ &beta;&beta; || || TT -- TT &OverBar;&OverBar; || || DD. 22 }} -- -- -- (( 3.13.1 )) ;; (( GG LL nno ++ 11 &CenterDot;&Center Dot; TT )) (( ythe y 00 )) == PP &Integral;&Integral; 00 LL Xx nno ++ 11 (( xx ,, ythe y 00 )) SS (( TT (( xx ,, ythe y 00 )) ,, vv 00 )) dd xx == AA (( ythe y ,, vv 00 )) ,, ythe y 00 &Element;&Element; (( 00 ,, WW )) (( GG WW nno ++ 11 &CenterDot;&CenterDot; TT )) (( xx 00 )) == PP &Integral;&Integral; 00 WW Xx nno ++ 11 (( xx 00 ,, ythe y )) SS (( TT (( xx 00 ,, ythe y )) ,, vv 00 )) dd ythe y == BB (( xx ,, vv 00 )) ,, xx 00 &Element;&Element; (( 00 ,, LL )) -- -- -- (( 3.23.2 )) ;; 式中,表示迭代时使用的算子;若Tn+1(x,y)∈Trange,取β=β0并跳出此次迭代,否则更新β←2β,再次计算Tn+1(x,y);In the formula, Indicates the operator used during iteration; if T n+1 (x, y)∈T range , take β=β 0 and jump out of this iteration, otherwise update β←2β, and calculate T n+1 (x, y) again ; 4)对于足够大的数n,满足终止准则:4) For a sufficiently large number n, the termination criterion is met: ||(Xn+1,Tn+1)-(Xn,Tn)||D<ε(1);||(X n+1 ,T n+1 )-(X n ,T n )|| D <ε(1); 或n=Nmax则迭代终止,(Xn+1,Tn+1)作为浓度场和温度场最终解;否则更新Tn←Tn+1、n←n+1,重复步骤2)~4)。or n=N max , the iteration terminates, and (X n+1 , T n+1 ) is used as the final solution of the concentration field and temperature field; otherwise, update T n ←T n+1 , n←n+1, and repeat step 2)~ 4). 2.根据权利要求1所述基于光谱吸收的温度场和浓度场重建的交替迭代算法,其特征在于,在待测区域的每一个方向上充分利用包含多条气体特征吸收谱线的信息,将选取的第r条气体特征吸收谱线对应的中心频率记为vr,从而式(2.1)、式(2.2)、式(3.1)和式(3.2)分别使用式(5.1)、式(5.2)、式(6.1)和式(6.2)替代:2. according to claim 1, the alternating iterative algorithm based on the temperature field and concentration field reconstruction of spectral absorption is characterized in that, on each direction of region to be measured, make full use of the information that comprises a plurality of gas characteristic absorption lines, will The center frequency corresponding to the selected rth gas characteristic absorption line is denoted as v r , so formula (2.1), formula (2.2), formula (3.1) and formula (3.2) use formula (5.1) and formula (5.2) respectively , Equation (6.1) and Equation (6.2) replace: Xx nno ++ 11 == argarg minmin Xx {{ || || KK LL ,, rr nno &CenterDot;&CenterDot; Xx -- AA rr || || (( 00 ,, WW )) 22 ++ || || KK WW ,, rr nno &CenterDot;&CenterDot; Xx -- BB rr || || (( 00 ,, LL )) 22 ++ &mu;&mu; || || Xx -- Xx &OverBar;&OverBar; || || DD. 22 }} -- -- -- (( 5.15.1 )) ;; (( KK LL ,, rr nno &CenterDot;&Center Dot; Xx )) (( ythe y 00 )) == PP &Integral;&Integral; 00 LL Xx (( xx ,, ythe y 00 )) SS (( TT nno (( xx ,, ythe y 00 )) ,, vv rr )) dd xx == AA rr (( ythe y 00 ,, vv rr )) ,, ythe y 00 &Element;&Element; (( 00 ,, WW )) (( KK WW ,, rr nno &CenterDot;&Center Dot; Xx )) (( xx 00 )) == PP &Integral;&Integral; 00 WW Xx (( xx 00 ,, ythe y )) SS (( TT nno (( xx 00 ,, ythe y )) ,, vv rr )) dd ythe y == BB rr (( xx 00 ,, vv rr )) ,, xx 00 &Element;&Element; (( 00 ,, LL )) -- -- -- (( 5.25.2 )) ;; TT nno ++ 11 == argarg minmin TT {{ || || GG LL ,, rr nno ++ 11 &CenterDot;&Center Dot; TT -- AA rr || || (( 00 ,, WW )) 22 ++ || || GG WW ,, rr nno ++ 11 &CenterDot;&CenterDot; TT -- BB rr || || (( 00 ,, LL )) 22 ++ &beta;&beta; || || TT -- TT &OverBar;&OverBar; || || DD. 22 }} -- -- -- (( 6.16.1 )) ;; (( GG LL ,, rr nno ++ 11 &CenterDot;&Center Dot; TT )) (( ythe y 00 )) == PP &Integral;&Integral; 00 LL Xx nno ++ 11 (( xx ,, ythe y 00 )) SS (( TT (( xx ,, ythe y 00 )) ,, vv rr )) dd xx == AA rr (( ythe y ,, vv rr )) ,, ythe y 00 &Element;&Element; (( 00 ,, WW )) (( GG WW ,, rr nno ++ 11 &CenterDot;&CenterDot; TT )) (( xx 00 )) == PP &Integral;&Integral; 00 WW Xx nno ++ 11 (( xx 00 ,, ythe y )) SS (( TT (( xx 00 ,, ythe y )) ,, vv rr )) dd ythe y == BB rr (( xx ,, vv rr )) ,, xx 00 &Element;&Element; (( 00 ,, LL )) -- -- -- (( 6.26.2 )) .. 3.根据权力要求2所述基于光谱吸收的温度场和浓度场重建的交替迭代算法,其特征在于,对待测区域进行网格离散化处理,并采用自适应迭代方法来求解每个网格内的浓度和温度,求解过程为:3. according to claim 2, based on the alternating iterative algorithm of temperature field and concentration field reconstruction of spectral absorption, it is characterized in that, carry out grid discretization processing in the area to be measured, and adopt self-adaptive iterative method to solve each grid concentration and temperature, the solution process is: 1)根据待测二维区域D的形状和大小,将待测二维区域划分成M行和N列的网格,令M=N,且每个网格分别对应一个浓度和温度待测值,从光谱数据库中选择I条气体特征吸收谱线,并且I≥[2×M×N/(M+N)],r的取值为1至I之间的整数;1) According to the shape and size of the two-dimensional area D to be measured, divide the two-dimensional area to be measured into grids of M rows and N columns, let M=N, and each grid corresponds to a concentration and temperature to be measured , select I gas characteristic absorption line from spectral database, and I≥[2×M×N/(M+N)], the value of r is an integer between 1 and 1; 2)式(5.2)写成:2) Formula (5.2) is written as: EgS(T,vr)X=P(vr)(7);EgS(T,v r )X=P(v r )(7); 式中,P(vr)为谱线vr对应的测量值投影向量,E=(e(i,j))是2N×N2维的0-1矩阵,其中e(i,j)表示激光是否通过第i个方向上的第j个格子,当第i个方向上的激光通过第j个格子时,令e(i,j)=1,否则e(i,j)=0;In the formula, P(v r ) is the measured value projection vector corresponding to the spectral line v r , E=(e (i, j) ) is a 2N×N 2 -dimensional 0-1 matrix, where e (i, j) represents Whether the laser passes through the j-th grid in the i-th direction, when the laser in the i-th direction passes through the j-th grid, set e (i, j) = 1, otherwise e (i, j) = 0; 式(7)的显式解表示为:The explicit solution of formula (7) is expressed as: Xx nno ++ 11 == (( AA nno TT AA nno ++ &alpha;&alpha; II )) -- 11 (( AA nno TT PP ++ &alpha;&alpha; Xx &OverBar;&OverBar; )) -- -- -- (( 88 )) ;; 其中,in, 通过式(8),由Tn(x,y)计算得到Xn+1(x,y);Through formula (8), X n+1 (x, y) can be calculated from T n (x, y); 3)由步骤2)计算得到的Xn+1(x,y)作为已知量,使用非线性最小二乘寻优算法对式(6.1)求解可得Tn+1(x,y)。3) X n+1 (x, y) calculated from step 2) is used as a known quantity, and T n+1 (x, y) can be obtained by solving formula (6.1) using nonlinear least squares optimization algorithm. 4.根据权利要求1所述基于光谱吸收的温度场和浓度场重建的交替迭代算法,其特征在于:给定X(x,y)和T(x,y)的容许集合Xrange×Trange,使其包含了精确解X*(x,y)和T*(x,y),同时引进带有正则化参数μ,β的罚项来克服重建过程的病态性,在每一步迭代中自动调整正则化参数μ,β,从而保证迭代解收敛于精确解。4. The alternate iterative algorithm for rebuilding temperature field and concentration field based on spectral absorption according to claim 1, characterized in that: given X (x, y) and T (x, y) allowable set X range × T range , so that it contains the exact solutions X * (x, y) and T * (x, y), and at the same time introduces a penalty term with regularization parameters μ, β to overcome the ill-conditioned nature of the reconstruction process, and automatically Adjust the regularization parameters μ, β to ensure that the iterative solution converges to the exact solution.
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